Overview of Advanced Methods of Reinforcement Learning in Finance
Machine Learning and Reinforcement Learning in Finance,
In the last course of our specialization, Overview of Advanced Methods of Reinforcement Learning in Finance, we will take a deeper look into topics discussed in our third course, Reinforcement Learning in Finance. In particular, we will talk about links between Reinforcement Learning, option pricing and physics, implications of Inverse Reinforcement Learning for modeling market impact and price dynamics, and perception-action cycles in Reinforcement Learning. Finally, we will overview trending and potential applications of Reinforcement Learning for high-frequency trading, cryptocurrencies, peer-to-peer lending, and more. After taking this course, students will be able to - explain fundamental concepts of finance such as market equilibrium, no arbitrage, predictability, - discuss market modeling, - Apply the methods of Reinforcement Learning to high-frequency trading, credit risk peer-to-peer lending, and cryptocurrencies trading.
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Rating | 3.3★ based on 9 ratings |
---|---|
Length | 5 weeks |
Starts | Jul 3 (39 weeks ago) |
Cost | $49 |
From | New York University Tandon School of Engineering, New York University via Coursera |
Instructor | Igor Halperin |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Algorithms Machine Learning |
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What people are saying
interesting deep dive into
Interesting deep dive into a RL application in Finance at forefront of research, however be prepared for challenging project assignments with limited support or guidance.
limited support or guidance
practical uses you may
Assessments are once again out of touch with the materials that have been presented and do not reflect any practical uses you may need to work on in the industry.
prepared for challenging project
finance at forefront
skip this certificate
Skip this certificate until fixed.
certificate until fixed
however be prepared
little more time
Lecture should spend a little more time in holding the attention of the student.
real follow up
real follow up by the team, and the assignments have nothing to do with the classes.
reflect any practical
rl application
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Rating | 3.3★ based on 9 ratings |
---|---|
Length | 5 weeks |
Starts | Jul 3 (39 weeks ago) |
Cost | $49 |
From | New York University Tandon School of Engineering, New York University via Coursera |
Instructor | Igor Halperin |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Algorithms Machine Learning |
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